While advances in computing resources have made processing enormous amounts of data
possible, human ability to identify patterns in such data has not scaled accordingly. Efficient …

Explosive growth in geospatial and temporal data as well as the emergence of new
technologies emphasize the need for automated discovery of spatiotemporal knowledge …

Profiling data to determine metadata about a given dataset is an important and frequent
activity of any IT professional and researcher and is necessary for various use-cases. It …

One of the major problems in pattern mining is the explosion of the number of results. Tight
constraints reveal only common knowledge, while loose constraints lead to an explosion in …

Exploratory Data Analysis (EDA) is an essential yet highly demanding task. To get a head
start before exploring a new dataset, data scientists often prefer to view existing EDA …

Summarization has been proven to be a useful and effective technique supporting data
analysis of large amounts of data. Knowledge discovery from data (KDD) is time consuming …

Anomaly extraction is an important problem essential to several applications ranging from
root cause analysis, to attack mitigation, and testing anomaly detectors. Anomaly extraction …

Parallel and distributed computing for cybersecurity Page 1 IEEE DISTRIBUTED SYSTEMS
ONLINE 1541-4922 © 2005 Published by the IEEE Computer Society Vol. 6, No. 10; …

A new distributed environment at less financial expenditure on communication over the
Internet is presented by cloud computing. In recent times, the increased number of users has …

Automatic and interactive data analysis is instrumental in making use of increasing amounts
of complex data. Owing to novel sensor modalities, analysis of data generated in …